Cognizant is hiring experienced technology professionals across multiple skills, business units and locations in India. According to the hiring information provided, these opportunities are available across Chennai, Bangalore, Noida, Kolkata, Hyderabad, Coimbatore and Pan India, with experience requirements ranging from 3 to 20 years. The listed openings are stated to be valid until 25 August 2026.
📅 Application validity: Until 25 August 2026
📍 Locations: Chennai | Bangalore | Noida | Kolkata | Hyderabad | Coimbatore | Pan India
💼 Experience: 3–20 Years
🏢 Company: Cognizant
🔥 Major Openings
The hiring list covers a wide range of technology positions, including Reltio MDM, AIML Data Scientist, Gen AI Engineer, MLOps Engineer, Gen AI Architect, AWS DevOps, Databricks + PySpark, GCP BigQuery, Snowflake DBT, Azure Data Engineering, Python, Kafka + Java, Data Engineering, Talend, Nifi + SQL, AWS + PySpark, Snowflake + GenAI, MSTR Admin and airline-domain QA.
It also includes specialized opportunities such as Automation Testing in Airline DCS/GDS/Loyalty, Mobile Functional Testing in Airline Booking, Performance Testing using JMeter/LoadRunner, IDBS Developer, LabWare, LabVantage, LIMS Testing, StarLIMS, Sample Manager, Tulip, CDS, Technical Full Stack Educator, Workday Reporting/Prism, Workday HCM Advanced Compensation, Workday Extend Consultant, SAP ABAP + RAP and SAP ABAP HANA + OData + CDS View.
🏢 About Cognizant
Cognizant is a global technology and professional-services company that helps enterprises modernize technology, reimagine processes and transform customer experiences. The company operates across more than 40 countries with 350,000+ employees and works across AI, cloud, software engineering, automation and digital transformation.
India is particularly important to Cognizant’s global workforce. Its 2024 sustainability report recorded approximately 241,500 employees in India, making the country a major technology delivery and engineering hub for the organization.
⭐ Why These Roles Are Good for Experienced Professionals
The biggest advantage of this hiring drive is technology breadth. Candidates are not limited to traditional application-development roles. The list includes modern areas such as GenAI, MLOps, data engineering, Databricks, Snowflake, cloud DevOps and AI-enabled data platforms alongside enterprise technologies such as SAP, Workday and MDM.
For senior professionals, this can be valuable because the roles often combine hands-on engineering with architecture, platform ownership, automation, data strategy or client-facing responsibilities. Cognizant’s scale also provides potential exposure to large enterprise environments and global clients.
The airline-testing positions are particularly interesting for QA professionals because they combine domain expertise with DCS/GDS, loyalty, mobile booking and performance testing. This is a strong combination for testers targeting specialized travel and airline technology careers.
🧰 Skills Candidates Should Highlight
- AI/ML: Python, machine learning, GenAI concepts, LLMs, prompt engineering, RAG, vector databases, model evaluation and deployment.
- MLOps: ML lifecycle management, CI/CD, Docker, Kubernetes, cloud platforms, model monitoring and automation.
- Data Engineering: Python, PySpark, SQL, Databricks, Kafka, Snowflake, DBT, BigQuery and data modelling.
- Cloud/DevOps: AWS, Azure, GCP, infrastructure automation, Terraform, CI/CD and monitoring.
- QA/Airline Testing: Functional testing, automation, DCS/GDS, airline booking, loyalty, mobile testing, JMeter and LoadRunner.
- Enterprise Platforms: Reltio, SAP ABAP/RAP/OData/CDS, Workday, LabWare, LabVantage, LIMS and MSTR.
🎯 Expected Cognizant Interview Rounds
Cognizant does not use one identical interview process for every experienced position. Recent candidate reports describe combinations of coding/technical assessment, L1 technical, advanced technical/L2, managerial and HR rounds.
For these openings, candidates should prepare for:
- Round 1: Recruiter screening and profile validation.
- Round 2: Technical assessment or L1 technical interview.
- Round 3: Advanced technical or techno-managerial discussion.
- Round 4: Managerial/client discussion where applicable.
- Round 5: HR, compensation, notice period and documentation discussion.
🧠 Preparation Tips
GenAI candidates: Prepare one complete GenAI project—from data ingestion and RAG/prompt design through evaluation, deployment and monitoring. Don’t only explain ChatGPT or prompting.
Data Engineers: Practice PySpark optimization, partitioning, joins, SQL tuning, Databricks architecture, Snowflake, DBT and incremental pipelines. Be ready to design a reliable data platform.
MLOps: Revise model deployment, CI/CD, Docker, Kubernetes, monitoring, model drift and rollback strategies. Explain how you would move a model from development to production.
Cloud/DevOps: Prepare architecture scenarios involving AWS/Azure/GCP, Terraform, networking, security, containers, observability and disaster recovery.
QA professionals: Prepare airline-specific scenarios such as booking failures, duplicate PNRs, payment failures, loyalty-point calculations, DCS/GDS integration and high-volume performance testing.
SAP/Workday specialists: Focus heavily on project-specific configuration, integrations, troubleshooting and real implementation scenarios rather than generic definitions.
💰 Expected Salary Range
The supplied hiring list does not publish salary figures, and compensation will vary significantly by skill, CCA level, experience, location and client project. As a market reference, current salary data shows Cognizant Data Engineers around ₹5–9 LPA base pay, while reported Cognizant MLOps Engineer compensation is around ₹14–16 LPA in limited available data. Cognizant AI Engineer reports include approximately ₹11–13 LPA for 4–6 years and ₹21–24 LPA for 10–14 years.
For senior GenAI, MLOps, architecture and specialized data positions, compensation can be substantially higher. These figures are market references, not official salary ranges for these vacancies.
📄 Resume Tips
Create a skill-specific resume for each application. A GenAI Architect should lead with architecture, LLM/RAG, cloud and leadership; a Data Engineer should highlight pipelines, PySpark, SQL and platforms; an MLOps engineer should emphasize production ML, CI/CD and observability; and a QA candidate should highlight airline domain, automation, DCS/GDS or performance testing.
For every project, quantify impact: pipeline volume, latency reduction, automation percentage, cloud migration scale, model performance, test coverage or production reliability. Also clearly state years of experience with the exact technology because Cognizant’s hiring list is strongly experience- and skill-specific.
📩 How to Apply
👉 Application Link: Click Here
The hiring information states that these openings are valid until 25 August 2026. Candidates should verify the exact requisition and eligibility before applying because openings can close early based on business requirements.
Apply through Cognizant’s official India Careers portal and search using your exact skill, such as GenAI Engineer, MLOps Engineer, Data Engineer, AWS DevOps, Databricks, Workday, SAP or QA/Automation. Cognizant’s jobs portal currently lists thousands of opportunities across India and allows candidates to search by role and location.
🚀 Final Take: This is a broad experienced-hiring drive rather than a single job opening. The strongest strategy is to match your resume to one exact skill requirement, demonstrate real project ownership and prepare deeply for scenario-based technical questions. With openings spanning AI, data, cloud, DevOps, QA, enterprise applications and specialized platforms, experienced professionals should prioritize the role where their recent hands-on experience most closely matches the listed requirements.
